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Caio Almeida

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Caio Almeida & Jianqing Fan & Francesca Tang, 2021. "Can a Machine Correct Option Pricing Models?," Working Papers 2021-44, Princeton University. Economics Department..

    Cited by:

    1. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2024. "Machine-learning stock market volatility: Predictability, drivers, and economic value," International Review of Financial Analysis, Elsevier, vol. 94(C).
    2. Liu, Chen & Wang, Chao & Tran, Minh-Ngoc & Kohn, Robert, 2025. "A long short-term memory enhanced realized conditional heteroskedasticity model," Economic Modelling, Elsevier, vol. 142(C).

  2. Caio Almeida & Kim Ardison & René Garcia, 2020. "Nonparametric Assessment of Hedge Fund Performance," Post-Print hal-02550789, HAL.

    Cited by:

    1. David Ardia & Laurent Barras & Patrick Gagliardini & Olivier Scaillet, 2020. "Is it Alpha or Beta? Decomposing Hedge Fund Returns When Models are Misspecified," Swiss Finance Institute Research Paper Series 20-82, Swiss Finance Institute, revised May 2023.
    2. Milad Nozari, 2021. "Information content of the risk-free rate for the pricing kernel bound," Journal of Asset Management, Palgrave Macmillan, vol. 22(4), pages 267-276, July.
    3. Elisa Becker‐Foss, 2024. "Performance and reporting predictability of hedge funds," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2257-2278, September.
    4. Jin Yuan & Xianghui Yuan, 2023. "A Comprehensive Method for Ranking Mutual Fund Performance," SAGE Open, , vol. 13(2), pages 21582440231, May.
    5. Fletcher, Jonathan, 2021. "Evaluating the performance of U.S. international equity closed-end funds," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    6. Ghosh, Anisha & Julliard, Christian & Taylor, Alex. P, 2025. "An information-theoretic asset pricing model," LSE Research Online Documents on Economics 126155, London School of Economics and Political Science, LSE Library.

  3. René Garcia & Caio Almeida & Kym Ardison & Jose Vicente, 2016. "Nonparametric Tail Risk, Stock Returns and the Macroeconomy," CIRANO Working Papers 2016s-20, CIRANO.

    Cited by:

    1. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & David Gabauer, 2021. "Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Working Papers 202161, University of Pretoria, Department of Economics.
    2. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    3. Fatemeh Mojtahedi & Seyed Mojtaba Mojaverian & Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Tail Risk Transmission: A Study of Iran Food Industry," DEM Working Papers Series 189, University of Pavia, Department of Economics and Management.
    4. Cao, Ji & Rieger, Marc Oliver & Zhao, Lei, 2023. "Safety first, loss probability, and the cross section of expected stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 345-369.
    5. Caio Almeida & Kim Ardison & René Garcia, 2020. "Nonparametric Assessment of Hedge Fund Performance," Post-Print hal-02550789, HAL.
    6. Baruník, Jozef & Bevilacqua, Mattia & Tunaru, Radu, 2022. "Asymmetric network connectedness of fears," LSE Research Online Documents on Economics 108199, London School of Economics and Political Science, LSE Library.
    7. Gupta, Rangan & Sheng, Xin & Pierdzioch, Christian & Ji, Qiang, 2021. "Disaggregated oil shocks and stock-market tail risks: Evidence from a panel of 48 economics," Research in International Business and Finance, Elsevier, vol. 58(C).
    8. Ahelegbey, Daniel Felix & Giudici, Paolo & Mojtahedi, Fatemeh, 2021. "Tail risk measurement in crypto-asset markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    9. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Reneé van Eyden, 2023. "Climate risks and U.S. stock‐market tail risks: A forecasting experiment using over a century of data," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 228-244, June.
    10. Esteban Vanegas & Andrés Mora-Valencia, 2025. "Skew Index: a machine learning forecasting approach," Risk Management, Palgrave Macmillan, vol. 27(1), pages 1-60, February.
    11. Qian, Lihua & Zeng, Qing & Lu, Xinjie & Ma, Feng, 2022. "Global tail risk and oil return predictability," Finance Research Letters, Elsevier, vol. 47(PB).
    12. Scaillet, Olivier & Trojani, Fabio & Camponovo, Lorenzo, 2016. "Comments on : Nonparametric Tail Risk, Stock Returns and the Macroeconomy," Working Papers unige:84999, University of Geneva, Geneva School of Economics and Management.
    13. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    14. Serrano, Pedro & Vaello-Sebastià, Antoni & Vich-Llompart, M. Magdalena, 2024. "The international linkages of market risk perception," Journal of Multinational Financial Management, Elsevier, vol. 72(C).
    15. K. Victor Chow & Wanjun Jiang & Bingxin Li & Jingrui Li, 2020. "Decomposing the VIX: Implications for the predictability of stock returns," The Financial Review, Eastern Finance Association, vol. 55(4), pages 645-668, November.
    16. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    17. Ergun, Lerby M., 2023. "Extreme downside risk in the cross-section of asset returns," International Review of Financial Analysis, Elsevier, vol. 90(C).
    18. Prodosh Simlai, 2021. "Accrual mispricing, value-at-risk, and expected stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1487-1517, November.
    19. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2018. "Portfolio optimization based on stochastic dominance and empirical likelihood," Journal of Econometrics, Elsevier, vol. 206(1), pages 167-186.
    20. Leal, Laura Simonsen & Almeida, Caio, 2017. "An SDF Approach to Hedge Funds' Tail Risk:Evidence from Brazilian Funds," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    21. Todorov, Viktor, 2022. "Nonparametric jump variation measures from options," Journal of Econometrics, Elsevier, vol. 230(2), pages 255-280.
    22. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    23. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    24. Mora-Valencia, Andrés & Rodríguez-Raga, Santiago & Vanegas, Esteban, 2021. "Skew index: Descriptive analysis, predictive power, and short-term forecast," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  4. Caio Almeida & Axel Simonsen & José Valentim Vicente, 2012. "Forecasting Bond Yields with Segmented Term Structure Models," Working Papers Series 288, Central Bank of Brazil, Research Department.

    Cited by:

    1. Papadimitriou, Theophilos & Gogas, Periklis & Tabak, Benjamin M., 2013. "Complex networks and banking systems supervision," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4429-4434.
    2. Rogier Quaedvlieg & Peter Schotman, 2022. "Hedging Long-Term Liabilities [Pricing the Term Structure with Linear Regressions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 505-538.
    3. Carlos Castro-Iragorri & Juan Felipe Peña & Cristhian Rodríguez, 2021. "A Segmented and Observable Yield Curve for Colombia," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 10(2), pages 179-200.
    4. Lozano-Espitia, Ignacio & Julio-Román, J. Manuel, 2020. "Debt limits and fiscal space for some Latin American economies," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    5. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Papers 2003.05095, arXiv.org.
    6. Zura Kakushadze & Willie Yu, 2020. "Machine Learning Treasury Yields," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 1-65.
    7. Gordon H. Dash & Nina Kajiji & Domenic Vonella, 2018. "The role of supervised learning in the decision process to fair trade US municipal debt," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 139-168, June.
    8. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    9. Feng, Pan & Qian, Junhui, 2018. "Forecasting the yield curve using a dynamic natural cubic spline model," Economics Letters, Elsevier, vol. 168(C), pages 73-76.
    10. Bruno Martins, 2012. "Local Market Structure and Bank Competition: evidence from the Brazilian auto loan market," Working Papers Series 299, Central Bank of Brazil, Research Department.

  5. Caio Almeida & José Vicente, 2008. "Are Interest Rate Options Important for the Assessment of Interest Rate Risk?," Working Papers Series 179, Central Bank of Brazil, Research Department.

    Cited by:

    1. Wright, Jonathan H. & Zhou, Hao, 2009. "Bond risk premia and realized jump risk," Journal of Banking & Finance, Elsevier, vol. 33(12), pages 2333-2345, December.
    2. Realdon, Marco, 2009. ""Extended Black" term structure models," International Review of Financial Analysis, Elsevier, vol. 18(5), pages 232-238, December.
    3. Allan Jonathan da Silva & Jack Baczynski, 2024. "Exploring non-analytical affine jump-diffusion models for path-dependent interest rate derivatives," Computational Management Science, Springer, vol. 21(1), pages 1-32, June.
    4. Jang, Bong-Gyu & Yoon, Ji Hee, 2010. "Analytic valuation formulas for range notes and an affine term structure model with jump risks," Journal of Banking & Finance, Elsevier, vol. 34(9), pages 2132-2145, September.
    5. Fricke, Christoph & Menkhoff, Lukas, 2015. "Financial conditions, macroeconomic factors and disaggregated bond excess returns," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 80-94.
    6. Fricke, Christoph & Menkhoff, Lukas, 2014. "Financial conditions, macroeconomic factors and (un)expected bond excess returns," Discussion Papers 35/2014, Deutsche Bundesbank.
    7. Allan Jonathan da Silva & Jack Baczynski & José Valentim Machado Vicente, 2024. "A Stochastically Correlated Bivariate Square-Root Model," IJFS, MDPI, vol. 12(2), pages 1-24, March.
    8. João Caldeira & Guilherme Moura & André Santos, 2015. "Measuring Risk in Fixed Income Portfolios using Yield Curve Models," Computational Economics, Springer;Society for Computational Economics, vol. 46(1), pages 65-82, June.
    9. Azamat Abdymomunov & Filippo Curti, 2020. "Quantifying and Stress Testing Operational Risk with Peer Banks’ Data," Journal of Financial Services Research, Springer;Western Finance Association, vol. 57(3), pages 287-313, June.
    10. Abdymomunov, Azamat & Gerlach, Jeffrey, 2014. "Stress testing interest rate risk exposure," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 287-301.

  6. Almeida, Caio Ibsen Rodrigues de & Vicente, José, 2007. "The role of no-arbitrage on forecasting: lessons from a parametric term structure model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 657, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).

    Cited by:

    1. Marco Shinobu Matsumura & Ajax Reynaldo Bello Moreira & José Valentim Machado Vicente, 2010. "Forecasting the Yield Curve with Linear Factor Models," Working Papers Series 223, Central Bank of Brazil, Research Department.
    2. Jens H. E. Christensen & Francis X. Diebold & Glenn D. Rudebusch, 2008. "An arbitrage-free generalized Nelson-Siegel term structure model," Working Paper Series 2008-07, Federal Reserve Bank of San Francisco.
    3. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2011. "Properties of Foreign Exchange Risk Premiums," CEPR Discussion Papers 8503, C.E.P.R. Discussion Papers.
    4. Andrea Carriero & Lorenzo Ricci & Elisabetta Vangelista, 2022. "Expectations and term premia in EFSF bond yields," Working Papers 54, European Stability Mechanism.
    5. Carriero, Andrea & Kapetanios, George & Marcellino, Massimiliano, 2012. "Forecasting government bond yields with large Bayesian vector autoregressions," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2026-2047.
    6. Almeida, Caio & Ardison, Kym & Kubudi, Daniela, 2014. "Approximating Risk Premium on a Parametric Arbitrage-free Term Structure Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    7. Andrea Carriero & George Kapetanios & Massimiliano Marcellino, 2010. "Forecasting Government Bond Yields with Large Bayesian VARs," Working Papers 662, Queen Mary University of London, School of Economics and Finance.
    8. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Working Papers Series 146, Central Bank of Brazil, Research Department.
    9. Andrade, Sandro C. & Barrett, W. Brian, 2011. "Can broker-dealer client surveys provide signals for debt investing?," Journal of Banking & Finance, Elsevier, vol. 35(5), pages 1170-1178, May.
    10. Wali ULLAH & Khadija Malik BARI, 2018. "The Term Structure of Government Bond Yields in an Emerging Market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 5-28, September.
    11. Takamizawa, Hideyuki & 高見澤, 秀幸, 2015. "Impact of No-arbitrage on Interest Rate Dynamics," Working Paper Series G-1-5, Hitotsubashi University Center for Financial Research.
    12. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    13. Carriero, Andrea & Giacomini, Raffaella, 2011. "How useful are no-arbitrage restrictions for forecasting the term structure of interest rates?," Journal of Econometrics, Elsevier, vol. 164(1), pages 21-34, September.
    14. Bekker, Paul A., 2017. "Interpretable Parsimonious Arbitrage-free Modeling of the Yield Curve," Research Report 17009-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    15. Sarno, Lucio & Schneider, Paul & Wagner, Christian, 2010. "Properties of Foreign Exchange Risk Premia," MPRA Paper 21302, University Library of Munich, Germany.
    16. Kessler, Stephan & Scherer, Bernd, 2009. "Varying risk premia in international bond markets," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1361-1375, August.
    17. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
    18. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    19. Joyce, Michael A.S. & Lildholdt, Peter & Sorensen, Steffen, 2010. "Extracting inflation expectations and inflation risk premia from the term structure: A joint model of the UK nominal and real yield curves," Journal of Banking & Finance, Elsevier, vol. 34(2), pages 281-294, February.
    20. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    21. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2021. "No‐arbitrage priors, drifting volatilities, and the term structure of interest rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 495-516, August.
    22. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    23. Joao Frois Caldeira & Guilherme Valle Moura & Marcelo Savino Portugal, 2011. "Efficient Interest Ratecurve Estimation And Forecasting In Brazil," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 133, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    24. Márcio Poletti Laurini & Armênio Westin Neto, 2014. "Arbitrage in the Term Structure of Interest Rates: a Bayesian Approach," International Econometric Review (IER), Econometric Research Association, vol. 6(2), pages 77-99, September.
    25. Frank J. Fabozzi & Francesco A. Fabozzi & Diana Tunaru, 2023. "A comparison of multi-factor term structure models for interbank rates," Review of Quantitative Finance and Accounting, Springer, vol. 61(1), pages 323-356, July.
    26. Fausto Vieira & Fernando Chague, Marcelo Fernandes, 2016. "A dynamic Nelson-Siegel model with forward-looking indicators for the yield curve in the US," Working Papers, Department of Economics 2016_31, University of São Paulo (FEA-USP).
    27. Argyropoulos Efthymios & Tzavalis Elias, 2015. "Term spread regressions of the rational expectations hypothesis of the term structure allowing for risk premium effects," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 19(1), pages 49-70, February.
    28. Daniela Kubudi & José Valentim Vicente, 2016. "A Joint Model of Nominal and Real Yield Curves," Working Papers Series 452, Central Bank of Brazil, Research Department.
    29. Leite, André Luís & Filho, Romeu Braz Pereira Gomes & Vicente, José Valentim Machado, 2010. "Forecasting the yield curve: A statistical model with market survey data," International Review of Financial Analysis, Elsevier, vol. 19(2), pages 108-112, March.

  7. Felipe Pinheiro & Caio Almeida & José Vicente, 2007. "Um Modelo de Fatores Latentes com Variáveis Macroeconômicas para a Curva de Cupom Cambial," Working Papers Series 148, Central Bank of Brazil, Research Department.

    Cited by:

    1. Almeida, Thiago Ramos, 2024. "Estimating time-varying factors’ variance in the string-term structure model with stochastic volatility," Research in International Business and Finance, Elsevier, vol. 70(PA).
    2. Alessandra Pasqualina Viola & Margarida Sarmiento Gutierrez & Claudio Henrique Barbedo & Andre Luiz Carvalhal da Silva, 2013. "Impact of exchange rate swaps on the dollar coupon curve: an analysis according to principal components regression," Brazilian Business Review, Fucape Business School, vol. 10(1), pages 79-101, January.
    3. Barbedo, Claudio H.S. & de Melo, Eduardo F.L., 2012. "Joint dynamics of Brazilian interest rate yields and macro variables under a no-arbitrage restriction," Journal of Economics and Business, Elsevier, vol. 64(5), pages 364-376.
    4. Flávio de Freitas Val & Claudio Henrique da Silveira Barbedo & Marcelo Verdini Maia, 2011. "Inflation expectation and implicit inflation: does market research provide accurate measures?," Brazilian Business Review, Fucape Business School, vol. 8(3), pages 83-100, July.

  8. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Working Papers Series 146, Central Bank of Brazil, Research Department.

    Cited by:

    1. Varga, Gyorgy, 2009. "Teste de Modelos Estatísticos para a Estrutura a Termo no Brasil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 63(4), December.
    2. J. C. Arismendi-Zambrano & T. Ramos-Almeida & J. C. Reboredo & M. A. Rivera-Castro, 2020. "Identifying Statistical Arbitrage in Interest Rate Markets: A Genetic Algorithm Approach," Economics Department Working Paper Series n305-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    3. Varga, Gyorgy, 2009. "Teste de Modelos Estatísticos para a Estrutura a Termo no Brasil [Test of Term Structure Models for Brazil]," MPRA Paper 20832, University Library of Munich, Germany.
    4. Joao Frois Caldeira & Guilherme Valle Moura & Marcelo Savino Portugal, 2011. "Efficient Interest Ratecurve Estimation And Forecasting In Brazil," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 133, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

  9. Caio Ibsen R. Almeida & José Valentim M. Vicente, 2007. "Identifying Volatility Risk Premium from Fixed Income Asian Options," Working Papers Series 136, Central Bank of Brazil, Research Department.

    Cited by:

    1. Almeida, Caio & Vicente, José, 2009. "Are interest rate options important for the assessment of interest rate risk?," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1376-1387, August.
    2. Vicente, José Valentim Machado & Guillen, Osmani Teixeira de Carvalho, 2013. "Do inflation-linked bonds contain information about future inflation?," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 67(2), June.
    3. Markellos, Raphael N. & Psychoyios, Dimitris, 2018. "Interest rate volatility and risk management: Evidence from CBOE Treasury options," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 190-202.
    4. Kellard, Neil & Dunis, Christian & Sarantis, Nicholas, 2010. "Foreign exchange, fractional cointegration and the implied-realized volatility relation," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 882-891, April.
    5. Duyvesteyn, Johan & de Zwart, Gerben, 2015. "Riding the swaption curve," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 57-75.
    6. Marins, Jaqueline Terra Moura & Vicente, José Valentim Machado, 2017. "Do the central bank actions reduce interest rate volatility?," Economic Modelling, Elsevier, vol. 65(C), pages 129-137.
    7. Caio Almeida & Jos� Vicente, 2012. "Term structure movements implicit in Asian option prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 119-134, February.
    8. Matsumura, Marco S. & Vicente, José Valentim Machado, 2010. "The role of macroeconomic variables in sovereign risk," Emerging Markets Review, Elsevier, vol. 11(3), pages 229-249, September.
    9. Kellard, Neil M. & Jiang, Ying & Wohar, Mark, 2015. "Spurious long memory, uncommon breaks and the implied–realized volatility puzzle," Journal of International Money and Finance, Elsevier, vol. 56(C), pages 36-54.

  10. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Does Curvature Enhance Forecasting?," Working Papers Series 155, Central Bank of Brazil, Research Department.

    Cited by:

    1. Almeida, Caio & Gomes, Romeu & Leite, André & Vicente, José, 2008. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 62(4), December.
    2. Marco Shinobu Matsumura & Ajax Reynaldo Bello Moreira & José Valentim Machado Vicente, 2010. "Forecasting the Yield Curve with Linear Factor Models," Working Papers Series 223, Central Bank of Brazil, Research Department.
    3. Rafael Barros de Rezende, 2011. "Giving Flexibility to the Nelson-Siegel Class of Term Structure Models," Brazilian Review of Finance, Brazilian Society of Finance, vol. 9(1), pages 27-49.
    4. Mr. Rodrigo Cabral & Mr. Richard Munclinger & Mr. Luiz Alves & Mr. Marco Rodriguez Waldo, 2011. "On Brazil’s Term Structure: Stylized Facts and Analysis of Macroeconomic Interactions," IMF Working Papers 2011/113, International Monetary Fund.
    5. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    6. Badics, Milan Csaba & Huszar, Zsuzsa R. & Kotro, Balazs B., 2023. "The impact of crisis periods and monetary decisions of the Fed and the ECB on the sovereign yield curve network," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    7. Almeida, Caio & Lund, Bruno, 2014. "Immunization of Fixed-Income Portfolios Using an Exponential Parametric Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    8. Flávio de Freitas Val & Claudio Henrique da Silveira Barbedo & Marcelo Verdini Maia, 2011. "Inflation expectation and implicit inflation: does market research provide accurate measures?," Brazilian Business Review, Fucape Business School, vol. 8(3), pages 83-100, July.
    9. Caldeira, João F. & Laurini, Márcio P. & Portugal, Marcelo S., 2010. "Bayesian Inference Applied to Dynamic Nelson-Siegel Model with Stochastic Volatility," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 30(1), October.
    10. Matsumura, Marco & Moreira, Ajax & Vicente, José, 2011. "Forecasting the yield curve with linear factor models," International Review of Financial Analysis, Elsevier, vol. 20(5), pages 237-243.
    11. Leite, André Luís & Filho, Romeu Braz Pereira Gomes & Vicente, José Valentim Machado, 2010. "Forecasting the yield curve: A statistical model with market survey data," International Review of Financial Analysis, Elsevier, vol. 19(2), pages 108-112, March.
    12. Joao Frois Caldeira & Guilherme Valle Moura & Marcelo Savino Portugal, 2011. "Efficient Interest Ratecurve Estimation And Forecasting In Brazil," Anais do XXXVII Encontro Nacional de Economia [Proceedings of the 37th Brazilian Economics Meeting] 133, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

  11. Caio Ibsen R. Almeida & José Valentim M. Vicente, 2006. "Term Structure Movements Implicit in Option Prices," Working Papers Series 128, Central Bank of Brazil, Research Department.

    Cited by:

    1. Vicente, José & Tabak, Benjamin M., 2008. "Forecasting bond yields in the Brazilian fixed income market," International Journal of Forecasting, Elsevier, vol. 24(3), pages 490-497.
    2. Almeida, Caio & Vicente, José, 2009. "Are interest rate options important for the assessment of interest rate risk?," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1376-1387, August.
    3. José Valentim Machado Vicente, 2021. "A Non-Knotty Inflation Risk Premium Model," Working Papers Series 543, Central Bank of Brazil, Research Department.
    4. Daniela Kubudi & José Valentim Vicente, 2016. "A Joint Model of Nominal and Real Yield Curves," Working Papers Series 452, Central Bank of Brazil, Research Department.
    5. Allan Jonathan da Silva & Jack Baczynski & José Valentim Machado Vicente, 2020. "Efficient Solutions for Pricing and Hedging Interest Rate Asian Options," Working Papers Series 513, Central Bank of Brazil, Research Department.

  12. Caio Almeida & Jeremy J. Graveline & Scott Joslin, 2005. "Do Options Contain Information About Excess Bond Returns?," IBMEC RJ Economics Discussion Papers 2005-04, Economics Research Group, IBMEC Business School - Rio de Janeiro.

    Cited by:

    1. Don H Kim, 2007. "Spanned stochastic volatility in bond markets: a reexamination of the relative pricing between bonds and bond options," BIS Working Papers 239, Bank for International Settlements.
    2. Jacobs, Kris & Karoui, Lotfi, 2009. "Conditional volatility in affine term-structure models: Evidence from Treasury and swap markets," Journal of Financial Economics, Elsevier, vol. 91(3), pages 288-318, March.
    3. Caio Almeida & José Vicente, 2008. "Are Interest Rate Options Important for the Assessment of Interest Rate Risk?," Working Papers Series 179, Central Bank of Brazil, Research Department.
    4. Collin-Dufresne, Pierre & Goldstein, Robert S. & Jones, Christopher S., 2009. "Can interest rate volatility be extracted from the cross section of bond yields?," Journal of Financial Economics, Elsevier, vol. 94(1), pages 47-66, October.
    5. Peter Feldhütter, 2016. "Can Affine Models Match the Moments in Bond Yields?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 1-56, June.
    6. Ruslan Bikbov & Mikhail Chernov, 2009. "Unspanned Stochastic Volatility in Affine Models: Evidence from Eurodollar Futures and Options," Management Science, INFORMS, vol. 55(8), pages 1292-1305, August.

Articles

  1. Caio Almeida & Jianqing Fan & Gustavo Freire & Francesca Tang, 2023. "Can a Machine Correct Option Pricing Models?," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(3), pages 995-1009, July.
    See citations under working paper version above.
  2. Almeida, Caio & Freire, Gustavo, 2022. "Pricing of index options in incomplete markets," Journal of Financial Economics, Elsevier, vol. 144(1), pages 174-205.

    Cited by:

    1. Wu, Lingke & Liu, Dehong & Yuan, Jianglei & Huang, Zhenhuan, 2022. "Implied volatility information of Chinese SSE 50 ETF options," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 609-624.
    2. Zhang, Aoran & Zhou, Chunyang, 2024. "A closed-form solution for spot volatility from options under limited data," Finance Research Letters, Elsevier, vol. 67(PA).
    3. Shuzhen Yang & Wenqing Zhang, 2024. "Asset pricing under model uncertainty with finite time and states," Papers 2408.13048, arXiv.org.
    4. Ghanbari, Hamed, 2024. "Persistent and transient variance components in option pricing models with variance-dependent Kernel," Journal of Empirical Finance, Elsevier, vol. 79(C).

  3. Almeida, Caio & Ardison, Kym & Garcia, René, 2020. "Nonparametric assessment of hedge fund performance," Journal of Econometrics, Elsevier, vol. 214(2), pages 349-378.
    See citations under working paper version above.
  4. Almeida, Caio & Brandao, Diego, 2019. "Measuring Long Run Risks for Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 39(1), July.

    Cited by:

    1. Almeida, Caio & Cordeiro, Fernando, 2019. "Long-term Yields Implied by Stochastic Discount Factor Decompositions," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 39(1), July.

  5. Faria, Adriano & Almeida, Caio, 2018. "A hybrid spline-based parametric model for the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 86(C), pages 72-94.

    Cited by:

    1. Zhang Chen & Ibrahim Sakouba, 2021. "Impact of the number of bonds on bond portfolio exposure to interest rate risk," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 4777-4797, July.
    2. Sabit Khakimzhanov & Yerulan Mustafin & Olzhas Kubenbayev & Dulat Atabek, 2019. "Constructing a Yield Curve in a Market with Low Liquidity," Russian Journal of Money and Finance, Bank of Russia, vol. 78(4), pages 71-98, December.
    3. Martin M. Andreasen & Jens H.E. Christensen & Glenn D. Rudebusch, 2017. "Term Structure Analysis with Big Data," CREATES Research Papers 2017-31, Department of Economics and Business Economics, Aarhus University.
    4. Piero C. Kauffmann & Hellinton H. Takada & Ana T. Terada & Julio M. Stern, 2022. "Learning Forecast-Efficient Yield Curve Factor Decompositions with Neural Networks," Econometrics, MDPI, vol. 10(2), pages 1-15, March.
    5. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.
    6. Andreasen, Martin M. & Christensen, Jens H.E. & Rudebusch, Glenn D., 2019. "Term Structure Analysis with Big Data: One-Step Estimation Using Bond Prices," Journal of Econometrics, Elsevier, vol. 212(1), pages 26-46.

  6. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    See citations under working paper version above.
  7. Caio Almeida & René Garcia, 2017. "Economic Implications of Nonlinear Pricing Kernels," Management Science, INFORMS, vol. 63(10), pages 3361-3380, October.

    Cited by:

    1. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    2. Milad Nozari, 2021. "Information content of the risk-free rate for the pricing kernel bound," Journal of Asset Management, Palgrave Macmillan, vol. 22(4), pages 267-276, July.
    3. Caio Almeida & Kim Ardison & René Garcia, 2020. "Nonparametric Assessment of Hedge Fund Performance," Post-Print hal-02550789, HAL.
    4. Bertille Antoine & Prosper Dovonon, 2017. "Robust Estimation With Exponentially Tilted Hellinger Distance," Discussion Papers dp17-15, Department of Economics, Simon Fraser University.
    5. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2019. "Too good to be true? Fallacies in evaluating risk factor models," Journal of Financial Economics, Elsevier, vol. 132(2), pages 451-471.
    6. Almeida, Caio & Freire, Gustavo, 2022. "Pricing of index options in incomplete markets," Journal of Financial Economics, Elsevier, vol. 144(1), pages 174-205.
    7. Korsaye, Sofonias Alemu & Trojani, Fabio & Vedolin, Andrea, 2023. "The global factor structure of exchange rates," Journal of Financial Economics, Elsevier, vol. 148(1), pages 21-46.
    8. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2018. "Portfolio optimization based on stochastic dominance and empirical likelihood," Journal of Econometrics, Elsevier, vol. 206(1), pages 167-186.
    9. Juzhi Zhang & Suresh P. Sethi & Tsan‐Ming Choi & T. C. E. Cheng, 2020. "Supply Chains Involving a Mean‐Variance‐Skewness‐Kurtosis Newsvendor: Analysis and Coordination," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1397-1430, June.
    10. Thierry Post & Iňaki Rodríguez Longarela, 2021. "Risk Arbitrage Opportunities for Stock Index Options," Operations Research, INFORMS, vol. 69(1), pages 100-113, January.
    11. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    12. Pascal J. Maenhout & Andrea Vedolin & Hao Xing, 2020. "Generalized Robustness and Dynamic Pessimism," NBER Working Papers 26970, National Bureau of Economic Research, Inc.

  8. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 333-376.
    See citations under working paper version above.
  9. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Rejoinder on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 418-426.

    Cited by:

    1. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & David Gabauer, 2021. "Forecasting Stock-Market Tail Risk and Connectedness in Advanced Economies Over a Century: The Role of Gold-to-Silver and Gold-to-Platinum Price Ratios," Working Papers 202161, University of Pretoria, Department of Economics.
    2. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    3. Fatemeh Mojtahedi & Seyed Mojtaba Mojaverian & Daniel Felix Ahelegbey & Paolo Giudici, 2020. "Tail Risk Transmission: A Study of Iran Food Industry," DEM Working Papers Series 189, University of Pavia, Department of Economics and Management.
    4. Cao, Ji & Rieger, Marc Oliver & Zhao, Lei, 2023. "Safety first, loss probability, and the cross section of expected stock returns," Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 345-369.
    5. Caio Almeida & Kim Ardison & René Garcia, 2020. "Nonparametric Assessment of Hedge Fund Performance," Post-Print hal-02550789, HAL.
    6. Baruník, Jozef & Bevilacqua, Mattia & Tunaru, Radu, 2022. "Asymmetric network connectedness of fears," LSE Research Online Documents on Economics 108199, London School of Economics and Political Science, LSE Library.
    7. Gupta, Rangan & Sheng, Xin & Pierdzioch, Christian & Ji, Qiang, 2021. "Disaggregated oil shocks and stock-market tail risks: Evidence from a panel of 48 economics," Research in International Business and Finance, Elsevier, vol. 58(C).
    8. Ahelegbey, Daniel Felix & Giudici, Paolo & Mojtahedi, Fatemeh, 2021. "Tail risk measurement in crypto-asset markets," International Review of Financial Analysis, Elsevier, vol. 73(C).
    9. Afees A. Salisu & Christian Pierdzioch & Rangan Gupta & Reneé van Eyden, 2023. "Climate risks and U.S. stock‐market tail risks: A forecasting experiment using over a century of data," International Review of Finance, International Review of Finance Ltd., vol. 23(2), pages 228-244, June.
    10. Esteban Vanegas & Andrés Mora-Valencia, 2025. "Skew Index: a machine learning forecasting approach," Risk Management, Palgrave Macmillan, vol. 27(1), pages 1-60, February.
    11. Qian, Lihua & Zeng, Qing & Lu, Xinjie & Ma, Feng, 2022. "Global tail risk and oil return predictability," Finance Research Letters, Elsevier, vol. 47(PB).
    12. Scaillet, Olivier & Trojani, Fabio & Camponovo, Lorenzo, 2016. "Comments on : Nonparametric Tail Risk, Stock Returns and the Macroeconomy," Working Papers unige:84999, University of Geneva, Geneva School of Economics and Management.
    13. Daniel Felix Ahelegbey, 2022. "Statistical Modelling of Downside Risk Spillovers," FinTech, MDPI, vol. 1(2), pages 1-10, April.
    14. Serrano, Pedro & Vaello-Sebastià, Antoni & Vich-Llompart, M. Magdalena, 2024. "The international linkages of market risk perception," Journal of Multinational Financial Management, Elsevier, vol. 72(C).
    15. K. Victor Chow & Wanjun Jiang & Bingxin Li & Jingrui Li, 2020. "Decomposing the VIX: Implications for the predictability of stock returns," The Financial Review, Eastern Finance Association, vol. 55(4), pages 645-668, November.
    16. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: Extracting what has been left," Journal of Financial Stability, Elsevier, vol. 53(C).
    17. Ergun, Lerby M., 2023. "Extreme downside risk in the cross-section of asset returns," International Review of Financial Analysis, Elsevier, vol. 90(C).
    18. Prodosh Simlai, 2021. "Accrual mispricing, value-at-risk, and expected stock returns," Review of Quantitative Finance and Accounting, Springer, vol. 57(4), pages 1487-1517, November.
    19. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2018. "Portfolio optimization based on stochastic dominance and empirical likelihood," Journal of Econometrics, Elsevier, vol. 206(1), pages 167-186.
    20. Leal, Laura Simonsen & Almeida, Caio, 2017. "An SDF Approach to Hedge Funds' Tail Risk:Evidence from Brazilian Funds," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    21. Todorov, Viktor, 2022. "Nonparametric jump variation measures from options," Journal of Econometrics, Elsevier, vol. 230(2), pages 255-280.
    22. Bevilacqua, Mattia & Tunaru, Radu, 2021. "The SKEW index: extracting what has been left," LSE Research Online Documents on Economics 108198, London School of Economics and Political Science, LSE Library.
    23. Freire, Gustavo, 2021. "Tail risk and investors’ concerns: Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    24. Mora-Valencia, Andrés & Rodríguez-Raga, Santiago & Vanegas, Esteban, 2021. "Skew index: Descriptive analysis, predictive power, and short-term forecast," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

  10. Faria, Adriano & Ornelas, Rafael & Almeida, Caio, 2016. "Empirical Selection of Optimal Portfolios and its Influence in the Estimation of Kreps-Porteus Utility Function Parameters," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(1), March.

    Cited by:

    1. Elminejad, Ali & Havranek, Tomas & Irsova, Zuzana, 2022. "Relative Risk Aversion: A Meta-Analysis," MetaArXiv b8uhe, Center for Open Science.
    2. Divino, Jose Angelo & Maciel, Daniel T.G.N. & Sosa, Wilfredo, 2020. "Government size, composition of public spending and economic growth in Brazil," Economic Modelling, Elsevier, vol. 91(C), pages 155-166.

  11. Almeida, Caio & Ricca, Bernardo & Tessari, Cristina, 2016. "Idiosyncratic Moments and the Cross-Section of Stock Returns in Brazil," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 36(2), November.

    Cited by:

    1. Berggrun, Luis & Cardona, Emilio & Lizarzaburu, Edmundo, 2024. "Evaluating asset pricing anomalies: Evidence from Latin America," Research in International Business and Finance, Elsevier, vol. 70(PB).

  12. Almeida, Caio & Lund, Bruno, 2014. "Immunization of Fixed-Income Portfolios Using an Exponential Parametric Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.

    Cited by:

    1. Victor Lapshin, 2019. "A Nonparametric Approach to Bond Portfolio Immunization," Mathematics, MDPI, vol. 7(11), pages 1-12, November.

  13. Almeida, Caio & Faria, Adriano, 2014. "Forecasting the Brazilian Term Structure Using Macroeconomic Factors," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(1), March.

    Cited by:

    1. Vieira, Fausto & Fernandes, Marcelo & Chague, Fernando, 2017. "Forecasting the Brazilian yield curve using forward-looking variables," International Journal of Forecasting, Elsevier, vol. 33(1), pages 121-131.
    2. Renata Tavanielli & Márcio Laurini, 2023. "Yield Curve Models with Regime Changes: An Analysis for the Brazilian Interest Rate Market," Mathematics, MDPI, vol. 11(11), pages 1-28, June.
    3. Lucélia Vaz & Rodrigo Raad, 2021. "Functional data analysis for brazilian term structure of interest rate," Textos para Discussão Cedeplar-UFMG 638, Cedeplar, Universidade Federal de Minas Gerais.

  14. Almeida, Caio & Ardison, Kym & Kubudi, Daniela, 2014. "Approximating Risk Premium on a Parametric Arbitrage-free Term Structure Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.

    Cited by:

    1. Luis Ceballos & Damián Romero, 2015. "Decomposing Long-Term Interest Rates: An International Comparison," Working Papers Central Bank of Chile 767, Central Bank of Chile.

  15. Caio Almeida & Jos� Vicente, 2012. "Term structure movements implicit in Asian option prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(1), pages 119-134, February.

    Cited by:

    1. Allan Jonathan da Silva & Jack Baczynski, 2024. "Exploring non-analytical affine jump-diffusion models for path-dependent interest rate derivatives," Computational Management Science, Springer, vol. 21(1), pages 1-32, June.
    2. Allan Jonathan da Silva & Jack Baczynski & Leonardo Fagundes de Mello, 2023. "Hedging Interest Rate Options with Reinforcement Learning: an investigation of a heavy-tailed distribution," Business and Management Studies, Redfame publishing, vol. 9(2), pages 1-14, December.
    3. Allan Jonathan da Silva & Jack Baczynski & José Valentim Machado Vicente, 2020. "Efficient Solutions for Pricing and Hedging Interest Rate Asian Options," Working Papers Series 513, Central Bank of Brazil, Research Department.
    4. Caio Almeida & José Vicente, 2008. "Are Interest Rate Options Important for the Assessment of Interest Rate Risk?," Working Papers Series 179, Central Bank of Brazil, Research Department.
    5. Xingchun Wang, 2020. "Analytical valuation of Asian options with counterparty risk under stochastic volatility models," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(3), pages 410-429, March.
    6. Allan Jonathan da Silva & Jack Baczynskiy & José Valentim M. Vicente, 2015. "A Discrete Monitoring Method for Pricing Asian Interest Rate Options," Working Papers Series 409, Central Bank of Brazil, Research Department.
    7. Alan De Genaro & Marco Avellaneda, 2018. "Pricing Interest Rate Derivatives Under Monetary Changes," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(06), pages 1-28, September.
    8. Daniela Kubudi & José Valentim Vicente, 2016. "A Joint Model of Nominal and Real Yield Curves," Working Papers Series 452, Central Bank of Brazil, Research Department.
    9. José Valentim Machado Vicente, 2021. "A Non-Knotty Inflation Risk Premium Model," Working Papers Series 543, Central Bank of Brazil, Research Department.

  16. Almeida, Caio & Garcia, René, 2012. "Assessing misspecified asset pricing models with empirical likelihood estimators," Journal of Econometrics, Elsevier, vol. 170(2), pages 519-537.

    Cited by:

    1. Thierry Post & Valerio Potì, 2017. "Portfolio Analysis Using Stochastic Dominance, Relative Entropy, and Empirical Likelihood," Management Science, INFORMS, vol. 63(1), pages 153-165, January.
    2. Schneider, Paul, 2019. "An anatomy of the market return," Journal of Financial Economics, Elsevier, vol. 132(2), pages 325-350.
    3. Lee, Seojeong, 2016. "Asymptotic refinements of a misspecification-robust bootstrap for GEL estimators," Journal of Econometrics, Elsevier, vol. 192(1), pages 86-104.
    4. Milad Nozari, 2021. "Information content of the risk-free rate for the pricing kernel bound," Journal of Asset Management, Palgrave Macmillan, vol. 22(4), pages 267-276, July.
    5. Francisco Peñaranda & Enrique Sentana, 2015. "A Unifying Approach to the Empirical Evaluation of Asset Pricing Models," Working Papers 488, Barcelona School of Economics.
    6. Caio Almeida & Kim Ardison & René Garcia, 2020. "Nonparametric Assessment of Hedge Fund Performance," Post-Print hal-02550789, HAL.
    7. Guidolin, Massimo & Thornton, Daniel L., 2018. "Predictions of short-term rates and the expectations hypothesis," International Journal of Forecasting, Elsevier, vol. 34(4), pages 636-664.
    8. La Vecchia, Davide & Moor, Alban & Scaillet, Olivier, 2023. "A higher-order correct fast moving-average bootstrap for dependent data," Journal of Econometrics, Elsevier, vol. 235(1), pages 65-81.
    9. Caio Almeida & René Garcia, 2017. "Economic Implications of Nonlinear Pricing Kernels," Management Science, INFORMS, vol. 63(10), pages 3361-3380, October.
    10. Bertille Antoine & Prosper Dovonon, 2017. "Robust Estimation With Exponentially Tilted Hellinger Distance," Discussion Papers dp17-15, Department of Economics, Simon Fraser University.
    11. Gagliardini, Patrick & Ronchetti, Diego, 2013. "Semi-parametric estimation of American option prices," Journal of Econometrics, Elsevier, vol. 173(1), pages 57-82.
    12. Beaulieu, Marie-Claude & Dufour, Jean-Marie & Khalaf, Lynda, 2025. "Identification-robust and simultaneous inference in multifactor asset pricing models," Journal of Econometrics, Elsevier, vol. 248(C).
    13. Marine Carrasco & N'Golo Koné, 2023. "Test for Trading Costs Effect in a Portfolio Selection Problem with Recursive Utility," CIRANO Working Papers 2023s-03, CIRANO.
    14. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2019. "Too good to be true? Fallacies in evaluating risk factor models," Journal of Financial Economics, Elsevier, vol. 132(2), pages 451-471.
    15. Xiaohong Chen & Lars Peter Hansen & Peter G. Hansen, 2020. "Robust identification of investor beliefs," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(52), pages 33130-33140, December.
    16. Patrick Gagliardini & Diego Ronchetti, 2020. "Comparing Asset Pricing Models by the Conditional Hansen-Jagannathan Distance," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 333-394.
    17. Gospodinov, Nikolay & Maasoumi, Esfandiar, 2021. "Generalized aggregation of misspecified models: With an application to asset pricing," Journal of Econometrics, Elsevier, vol. 222(1), pages 451-467.
    18. Yu, Xisheng, 2021. "A unified entropic pricing framework of option: Using Cressie-Read family of divergences," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    19. David le Bris & William N. Goetzmann & Sébastien Pouget, 2014. "Testing Asset Pricing Theory on Six Hundred Years of Stock Returns: Prices and Dividends for the Bazacle Company from 1372 to 1946," NBER Working Papers 20199, National Bureau of Economic Research, Inc.
    20. Gospodinov, Nikolay & Kan, Raymond & Robotti, Cesare, 2013. "Chi-squared tests for evaluation and comparison of asset pricing models," Journal of Econometrics, Elsevier, vol. 173(1), pages 108-125.
    21. Sentana, Enrique & Manresa, Elena & Penaranda, Francisco, 2017. "Empirical Evaluation of Overspecified Asset Pricing Models," CEPR Discussion Papers 12085, C.E.P.R. Discussion Papers.
    22. Liu, Yan, 2021. "Index option returns and generalized entropy bounds," Journal of Financial Economics, Elsevier, vol. 139(3), pages 1015-1036.
    23. J. Arismendi-Zambrano & R. Azevedo, 2020. "Implicit Entropic Market Risk-Premium from Interest Rate Derivatives," Economics Department Working Paper Series n303-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    24. Caio Almeida & Kym Ardison & René Garcia & Jose Vicente, 2017. "Nonparametric Tail Risk, Stock Returns, and the Macroeconomy," Journal of Financial Econometrics, Oxford University Press, vol. 15(3), pages 333-376.
    25. Chen, Xiaohong & Hansen, Lars Peter & Hansen, Peter G., 2024. "Robust inference for moment condition models without rational expectations," Journal of Econometrics, Elsevier, vol. 243(1).
    26. Sousa, João & Sousa, Ricardo M., 2017. "Predicting risk premium under changes in the conditional distribution of stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 50(C), pages 204-218.
    27. Seojeong Lee, 2018. "Asymptotic Refinements of a Misspecification-Robust Bootstrap for Generalized Empirical Likelihood Estimators," Papers 1806.00953, arXiv.org, revised Jun 2018.
    28. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
    29. Post, Thierry & Karabatı, Selçuk & Arvanitis, Stelios, 2018. "Portfolio optimization based on stochastic dominance and empirical likelihood," Journal of Econometrics, Elsevier, vol. 206(1), pages 167-186.
    30. Thierry Post & Iňaki Rodríguez Longarela, 2021. "Risk Arbitrage Opportunities for Stock Index Options," Operations Research, INFORMS, vol. 69(1), pages 100-113, January.
    31. Nikolay Gospodinov & Esfandiar Maasoumi, 2017. "General Aggregation of Misspecified Asset Pricing Models," FRB Atlanta Working Paper 2017-10, Federal Reserve Bank of Atlanta.
    32. Ghosh, Anisha & Julliard, Christian & Taylor, Alex. P, 2025. "An information-theoretic asset pricing model," LSE Research Online Documents on Economics 126155, London School of Economics and Political Science, LSE Library.

  17. Almeida, Caio & Graveline, Jeremy J. & Joslin, Scott, 2011. "Do interest rate options contain information about excess returns?," Journal of Econometrics, Elsevier, vol. 164(1), pages 35-44, September.

    Cited by:

    1. Hai Lin & Chunchi Wu & Guofu Zhou, 2018. "Forecasting Corporate Bond Returns with a Large Set of Predictors: An Iterated Combination Approach," Management Science, INFORMS, vol. 64(9), pages 4218-4238, September.
    2. Zhu, Xiaoneng, 2015. "Out-of-sample bond risk premium predictions: A global common factor," Journal of International Money and Finance, Elsevier, vol. 51(C), pages 155-173.
    3. Rui Liu, 2019. "Forecasting Bond Risk Premia with Unspanned Macroeconomic Information," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 9(01), pages 1-62, March.
    4. Fricke, Christoph & Menkhoff, Lukas, 2014. "Financial conditions, macroeconomic factors and (un)expected bond excess returns," Discussion Papers 35/2014, Deutsche Bundesbank.
    5. R. L�pez & E. Navarro, 2013. "Interest rate and stock return volatility indices for the Eurozone. Investors' gauges of fear during the recent financial crisis," Applied Financial Economics, Taylor & Francis Journals, vol. 23(18), pages 1419-1432, September.
    6. Peter Christoffersen & Christian Dorion & Kris Jacobs & Lotfi Karoui, 2014. "Nonlinear Kalman Filtering in Affine Term Structure Models," Cahiers de recherche 1404, CIRPEE.
    7. Peter Feldhütter & Christian Heyerdahl-Larsen & Philipp Illeditsch, 2018. "Risk Premia and Volatilities in a Nonlinear Term Structure Model [Quadratic term structure models: theory and evidence]," Review of Finance, European Finance Association, vol. 22(1), pages 337-380.
    8. Gregory R. Duffee, 2012. "Forecasting interest rates," Economics Working Paper Archive 599, The Johns Hopkins University,Department of Economics.
    9. Joslin, Scott & Konchitchki, Yaniv, 2018. "Interest rate volatility, the yield curve, and the macroeconomy," Journal of Financial Economics, Elsevier, vol. 128(2), pages 344-362.
    10. Monfort, Alain & Pegoraro, Fulvio & Renne, Jean-Paul & Roussellet, Guillaume, 2017. "Staying at zero with affine processes: An application to term structure modelling," Journal of Econometrics, Elsevier, vol. 201(2), pages 348-366.
    11. Fernandes, Marcelo & Vieira, Fausto, 2019. "A dynamic Nelson–Siegel model with forward-looking macroeconomic factors for the yield curve in the US," Journal of Economic Dynamics and Control, Elsevier, vol. 106(C), pages 1-1.
    12. Doshi, Hitesh & Jacobs, Kris & Liu, Rui, 2024. "Modeling volatility in dynamic term structure models," Journal of Financial Economics, Elsevier, vol. 161(C).
    13. Fricke, Christoph, 2012. "Expected and unexpected bond excess returns: Macroeconomic and market microstructure effects," Hannover Economic Papers (HEP) dp-493, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    14. J. Arismendi-Zambrano & R. Azevedo, 2020. "Implicit Entropic Market Risk-Premium from Interest Rate Derivatives," Economics Department Working Paper Series n303-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    15. Caio Almeida & Kym Ardison & Daniela Kubudi & Axel Simonsen & José Vicente, 2018. "Forecasting Bond Yields with Segmented Term Structure Models," Journal of Financial Econometrics, Oxford University Press, vol. 16(1), pages 1-33.
    16. Jonas Nygaard Eriksen, 2015. "Expected Business Conditions and Bond Risk Premia," CREATES Research Papers 2015-44, Department of Economics and Business Economics, Aarhus University.
    17. Scott Joslin & Anh Le, 2021. "Interest Rate Volatility and No-Arbitrage Affine Term Structure Models," Management Science, INFORMS, vol. 67(12), pages 7391-7416, December.
    18. Fricke, Christoph & Menkhoff, Lukas, 2015. "Financial conditions, macroeconomic factors and disaggregated bond excess returns," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 80-94.
    19. Anne Lundgaard Hansen, 2018. "Volatility-Induced Stationarity and Error-Correction in Macro-Finance Term Structure Modeling," Discussion Papers 18-12, University of Copenhagen. Department of Economics.
    20. Peter Feldhütter, 2016. "Can Affine Models Match the Moments in Bond Yields?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 1-56, June.
    21. Anders B. Trolle & Eduardo S. Schwartz, 2009. "A General Stochastic Volatility Model for the Pricing of Interest Rate Derivatives," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 2007-2057, May.

  18. Caio Almeida & Romeu Gomes & André Leite & Axel Simonsen & José Vicente, 2009. "Does Curvature Enhance Forecasting?," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 12(08), pages 1171-1196.
    See citations under working paper version above.
  19. Almeida, Caio & Vicente, José, 2009. "Are interest rate options important for the assessment of interest rate risk?," Journal of Banking & Finance, Elsevier, vol. 33(8), pages 1376-1387, August.
    See citations under working paper version above.
  20. Almeida, Caio & Vicente, José, 2009. "Identifying volatility risk premia from fixed income Asian options," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 652-661, April.
    See citations under working paper version above.
  21. Almeida, Caio & Vicente, José, 2008. "The role of no-arbitrage on forecasting: Lessons from a parametric term structure model," Journal of Banking & Finance, Elsevier, vol. 32(12), pages 2695-2705, December.
    See citations under working paper version above.
  22. Almeida, Caio & Gomes, Romeu & Leite, André & Vicente, José, 2008. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 62(4), December.
    See citations under working paper version above.
  23. Caio Ibsen Rodrigues de Almeida & Samy Dana, 2005. "Stochastic Volatility and Option Pricing in the Brazilian Stock Marke," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 4(2), pages 169-206, August.

    Cited by:

    1. Ramos, Antônio M.T. & Carvalho, J.A. & Vasconcelos, G.L., 2016. "Exponential model for option prices: Application to the Brazilian market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 161-168.
    2. Alok Dixit & Shivam Singh, 2018. "Ad-Hoc Black–Scholes vis-à-vis TSRV-based Black–Scholes: Evidence from Indian Options Market," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 16(1), pages 57-88, March.

  24. Caio Ibsen Rodrigues De Almeida, 2005. "Affine Processes, Arbitrage-Free Term Structures Of Legendre Polynomials, And Option Pricing," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 8(02), pages 161-184.

    Cited by:

    1. Almeida, Caio Ibsen Rodrigues de & Vicente, José, 2007. "The role of no-arbitrage on forecasting: lessons from a parametric term structure model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 657, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Almeida, Caio & Ardison, Kym & Kubudi, Daniela, 2014. "Approximating Risk Premium on a Parametric Arbitrage-free Term Structure Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    3. Varga, Gyorgy, 2009. "Teste de Modelos Estatísticos para a Estrutura a Termo no Brasil [Test of Term Structure Models for Brazil]," MPRA Paper 20832, University Library of Munich, Germany.

  25. Almeida, Caio Ibsen Rodrigues de, 2005. "A Note on the Relation Between Principal Components and Dynamic Factors in Affine Term Structure Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 25(1), May.

    Cited by:

    1. Michele Leonardo Bianchi, 2018. "Are multi-factor Gaussian term structure models still useful? An empirical analysis on Italian BTPs," Papers 1805.09996, arXiv.org.

  26. Caio Ibsen Rodrigues De Almeida, 2004. "Time-Varying Risk Premia In Emerging Markets: Explanation By A Multi-Factor Affine Term Structure Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(07), pages 919-947.

    Cited by:

    1. Mordecki, Ernesto & Rodríguez, Andrés Sosa, 2021. "Country risk for emerging economies: a dynamical index proposal with a case study," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(2), April.
    2. Mr. Rodrigo Cabral & Mr. Richard Munclinger & Mr. Luiz Alves & Mr. Marco Rodriguez Waldo, 2011. "On Brazil’s Term Structure: Stylized Facts and Analysis of Macroeconomic Interactions," IMF Working Papers 2011/113, International Monetary Fund.
    3. Almeida, Caio Ibsen Rodrigues de, 2005. "A Note on the Relation Between Principal Components and Dynamic Factors in Affine Term Structure Models," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 25(1), May.
    4. Juan Andr�s Espinosa Torres & Luis Fernando Melo Velandia & Jos� Fernando Moreno Guti�rrez, 2014. "Estimaci�n de la prima por vencimiento de los TES en pesos del gobierno colombiano," Borradores de Economia 12333, Banco de la Republica.
    5. Juan Andrés Espinosa Torres & Luis Fernando Melo Velandia & José Fernando Moreno Gutiérrez, 2014. "Estimación de la prima por vencimiento de los TES en pesos del gobierno colombiano," Borradores de Economia 854, Banco de la Republica de Colombia.
    6. Júlio Cesar Albuquerque Bastos & Gabriel Caldas Montes, 2011. "Metasde Inflação E Estrutura A Termo Das Taxas De Juros - Uma Análise Dainfluência Da Credibilidade Sobre O Spread Da Taxa De Juros De Longoprazo No Brasil," Anais do XXXVIII Encontro Nacional de Economia [Proceedings of the 38th Brazilian Economics Meeting] 142, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. Abdymomunov, Azamat & Gerlach, Jeffrey, 2014. "Stress testing interest rate risk exposure," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 287-301.

  27. Caio Ibsen Rodrigues De Almeida & Antonio Marcos Duarte & Cristiano Augusto Coelho Fernandes, 2003. "A Generalization Of Principal Component Analysis For Non-Observable Term Structures In Emerging Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 6(08), pages 885-903.

    Cited by:

    1. Almeida, Caio Ibsen Rodrigues de & Vicente, José, 2007. "The role of no-arbitrage on forecasting: lessons from a parametric term structure model," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 657, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    2. Caio Almeida & Romeu Gomes & André Leite & José Vicente, 2007. "Movimentos da Estrutura a Termo e Critérios de Minimização do Erro de Previsão em um Modelo Paramétrico Exponencial," Working Papers Series 146, Central Bank of Brazil, Research Department.
    3. Almeida, Caio & Lund, Bruno, 2014. "Immunization of Fixed-Income Portfolios Using an Exponential Parametric Model," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 34(2), November.
    4. Meres, Bernardo & Almeida, Caio, 2008. "Extracting Default Probabilities from Sovereign Bonds," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 28(1), May.

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